HerO 2 提升事实核查效率，运行速度最快且排名第二。
Team HUMANE at AVeriTeC 2025: HerO 2 for Efficient Fact Verification
- 通过摘要生成和答案重写提升证据质量
- 量化微调后在计算受限下仍保持高准确率
- 采用新语言模型骨架，适合实际部署
本文介绍 HerO 2，Team HUMANE 在 FEVER-25 工作坊的 AVeriTeC 共享任务中的系统。HerO 2 是去年挑战赛表现最佳开源模型 HerO 的升级版，通过文档摘要与答案重写提升证据质量，基于计算约束进行后训练量化优化真伪判断，同时集成更新的语言模型骨干网络以提升整体性能。该系统在排行榜中位列第二，且为前三名中运行时间最短，展现了高效性与实用潜力。代码已公开于 https://github.com/ssu-humane/HerO2。
原文摘要 · Abstract (English)
This paper presents HerO 2, Team HUMANE's system for the AVeriTeC shared task at the FEVER-25 workshop. HerO 2 is an enhanced version of HerO, the best-performing open-source model from the previous year's challenge. It improves evidence quality through document summarization and answer reformulation, optimizes veracity prediction via post-training quantization under computational constraints, and enhances overall system performance by integrating updated language model (LM) backbones. HerO 2 ranked second on the leaderboard while achieving the shortest runtime among the top three systems, demonstrating both high efficiency and strong potential for real-world fact verification. The code is available at https://github.com/ssu-humane/HerO2.
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